The Spatial and Temporal Variation Characteristics of CH4 and CO2 Emission Flux under Different Land Use Types in the Yellow River Delta Wetland

pdf
Số trang The Spatial and Temporal Variation Characteristics of CH4 and CO2 Emission Flux under Different Land Use Types in the Yellow River Delta Wetland 7 Cỡ tệp The Spatial and Temporal Variation Characteristics of CH4 and CO2 Emission Flux under Different Land Use Types in the Yellow River Delta Wetland 649 KB Lượt tải The Spatial and Temporal Variation Characteristics of CH4 and CO2 Emission Flux under Different Land Use Types in the Yellow River Delta Wetland 0 Lượt đọc The Spatial and Temporal Variation Characteristics of CH4 and CO2 Emission Flux under Different Land Use Types in the Yellow River Delta Wetland 0
Đánh giá The Spatial and Temporal Variation Characteristics of CH4 and CO2 Emission Flux under Different Land Use Types in the Yellow River Delta Wetland
5 ( 22 lượt)
Nhấn vào bên dưới để tải tài liệu
Để tải xuống xem đầy đủ hãy nhấn vào bên trên
Chủ đề liên quan

Nội dung

Journal of Geoscience and Environment Protection, 2015, 3, 26-32 Published Online August 2015 in SciRes. http://www.scirp.org/journal/gep http://dx.doi.org/10.4236/gep.2015.36005 The Spatial and Temporal Variation Characteristics of CH4 and CO2 Emission Flux under Different Land Use Types in the Yellow River Delta Wetland Qingfeng Chen, Junjian Ma, Changsheng Zhao, Rongbin Li Key Laboratory for Applied Technology of Sophisticated Analytical Instruments of Shandong Province, Shandong Provincial Analysis Test Center, Jinan, China Email: chensdcn@163.com Received 4 June 2015; accepted 19 August 2015; published 25 August 2015 Abstract The Yellow River Delta Wetland is one of the youngest wetlands, and also the most complete, extensive wetlands in China. The wetland in this delta is ecologically important due to their hydrologic attributes and their roles as ecotones between terrestrial and aquatic ecosystems. In the study, the spatial and temporal variation characteristics of CH4 and CO2 emission flux under five kinds of land use types in the wetland were investigated. The results indicated that the greenhouse gas emission flux, especially the CO2 and CH4, showed distinctly spatial and temporal variation under different land use types in the wetland. In the spring, the emission flux of CO2 was higher than that of CO2 in the autumn, and appeared negative in HW3 and HW4 in the autumn. CH4 emission flux of HW4 and HW5 was negative in the spring and autumn, which indicated that the CH4 emission process was net absorption. Among the five kinds of land use types, the CO2 emission flux of HW4 discharged the largest emission flux reaching 29.3 mg∙m−2∙h−1, but the CH4 emission flux of HW2 discharged the largest emission flux reaching 0.15 mg∙m−2∙h−1. From the estuary to the inland, the emission flux of CO2 was decreased at first and then appeared increasing trend, but the emission flux of CH4 was contrary to CO2. Keywords Wetland, CH4 and CO2, Emission Flux, Land Use, Spatial and Temporal Variation 1. Introduction Global warming has attracted wide attention and advanced research hotspot of global environmental problems, which is caused by increased greenhouse gas (GHG) emissions and the change of land use. Both CO2 and CH4 are considered as the most important greenhouse gases, accounting for 70% and 23% of the contribution to the temperature rising efficiency respectively [1]. How to cite this paper: Chen, Q.F., Ma, J.J., Zhao, C.S. and Li, R.B. (2015) The Spatial and Temporal Variation Characteristics of CH4 and CO2 Emission Flux under Different Land Use Types in the Yellow River Delta Wetland. Journal of Geoscience and Environment Protection, 3, 26-32. http://dx.doi.org/10.4236/gep.2015.36005 Q. F. Chen et al. Wetlands account for 6% of the world’s land surface [2] and play an important role in the global carbon cycle by acting as natural carbon sinks [3]. Wetlands contain about 12% of the global carbon pool, and are very close related to climate change [4]. Wetlands provide a productive ecosystem and favorable habitat for a wide variety of plants and animal species in the world. However, wetlands ecological systems are also ecologically sensitive and adaptive systems, and show enormous diversity according to their genesis, geographical location, water regime and chemistry, dominant species, and soil and sediment characteristics [5]. The Yellow River Delta, one of the largest deltas in China, is situated in the northeast of Shandong Province on the southern bank of the Bohai Sea [6]. The delta covers an area of 7870 km2 and is composed of large wetland areas, where the total area of the wetlands amounts to 4167 km2 [7]. Among the total wetlands, natural wetlands cover 3131 km2 (or 75.1% of the whole delta), and artificial wetlands cover 1036 km2 (or 24.9% of the study area) [8]. The Yellow River Delta Wetland is one of the youngest wetlands, and also the most complete, extensive wetlands in warm temperate area in China. The wetlands in this delta are ecologically important due to their hydrologic attributes and their role as ecotones between terrestrial and marine ecosystems [9]. In this study, the spatial and temporal variation characteristics of CH4 and CO2 emission flux under different land use types in the Yellow River Delta Wetland were investigated, including: 1) The variation characteristics of CH4 and CO2 emission flux under different seasons; 2) The variation characteristics of CH4 and CO2 emission flux under different years; 3) The variation characteristics of CH4 and CO2 emission flux under different land use types. This study may have a large contribution to the protection of new-born frangibility, typical habitat and biodiversity in the wetland ecological system. It will also be beneficial for investigating the influence of the wetland carbon storage change on the terrestrial ecosystem carbon cycle and the global climate change. 2. Materials and Methods 2.1. Site Description The study was conducted at the Yellow River Delta Wetland (N36˚55' - N38°16', E117˚31' - E119˚18'), which is located in the southern bank of the Bohai bay and western bank of the Bohai Sea (Figure 1). It belongs to the warm temperate and semi-humid monsoon climate zone, with 594.3 mm of mean annual precipitation, 2049.4 mm of average annual evaporation, 12.4˚C of mean annual temperature and 217.8 days of mean annual frostfree period. The soil types of this zone have high salinity, including tidal soil, saline tidal soil and coastal tidal soil. Tidal soil is neutral or alkalescence, and is mainly distributed along the river and south central plains. Salt soil distributes in the coastal areas, with a small amount of salt cultivated [10]. Figure 1. Location of the Yellow River Delta Wetland and sampling. 27 Q. F. Chen et al. 2.2. Sampling Sites Selection The monitoring sites and Lland use characteristics of the Yellow River Delta Wetland were shown in Figure2, Table 1 and Table 2 [10]. There were 10 sites of soil samples and 5 kinds of typical salt marsh plant communities as carbon emissions monitoring site, including beaches bare land, Suaeda salsa community, mixed community of Phragmites australis and Suaeda salsa, Phragmites australis community, Tamnrix chinesi community and farmland community. The five types of vegetation communities in Yellow River Delta Wetland are the most typical and representative, and have a zonal distributing phenomenon from the coastal to the inland [11] [12]. 2.3. Experimental Methods The emissions concentration and fluxes of CH4 and CO2 were measured by using the static opaque chamber-GC technique, an eddy covariance technique. Five sampling sites were selected to collect 0 - 20 cm of soil samples in every typical salt marsh plant community. The samples of soil, plants and water were stored at 4˚C and analyzed in 48 h after sampling. The other parameters, such as TN, TP, pH, and OM, were measured according to the Standard Methods of APHA [13] [14]. The frequency of samples was taken every quarter of one year. The method of vegetation coverage degree is quadrat sampling method. The size of quadrat is 100 cm × 100 cm. In the quadrat, every vegetation coverage degree can be obtained. Figure 2. Land use characteristics of the Yellow River Delta Wetland. 28 Q. F. Chen et al. Table 1. Soil sampling sites and description of ecosystem situation. Number Sampling site Longitude and latitude C1 Woodland E118˚55'32" N37˚45'96" Woodland ecosystem, the vegetation types are mainly poplars. C2 Cotton field E118˚55'39" N37˚46'11" Farmland ecosystem, the vegetation types are mainly cotton. C3 Imperata cylindrica community E118˚58'21" N37˚46'4" The vegetation types are mainly Imperata cylindrical and Phragmites australis, with 0.5 - 1.2 m of plant height and about 80% of cover degree. C4 Tamnrix chinesi community E118˚58'21" N37˚46'9" The vegetation types are mainly Tamnrix chinesi, with 0.5 - 2.5 m of plant height and about 60% of cover degree. C5 Tamnrix chinesi community E119˚1'1" N37˚45'51" The vegetation type is Phragmites australis, with 0.5 - 1.5 m of plant height and about 40% of cover degree. C6 Phragmites australi community E119˚04'07" N37˚45'90" The vegetation type is Phragmites australis, with 0.5 - 1.8 m of plant height and about 85% of cover degree. C7 Mixed community of Phragmites australi and Suaeda salsa E119˚9'20" N37˚44'48" The vegetation types are mainly Phragmites australis and Suaeda salsa, with 0.5 - 1.2 m of plant height and about 65% of cover degree. C8 Suaeda salsa community E119˚11'22" N37˚44'68" The vegetation types are mainly Suaeda salsa, with 0.5 - 1.0 m of plant height and about 45% of cover degree. C9 Beaches bare land E119˚13'44" N37˚43'04" The vegetation types are mainly Suaeda salsa, with 0.2 - 0.6 m of plant height and about 15% of cover degree. C10 Suaeda salsa community E119˚12'76" N37˚43'46" The vegetation types are mainly Suaeda, with 0.2 - 0.5 m of plant height and about 25% of cover degree. Description of ecosystem situation Table 2. Typical salt marsh plant community and description of ecosystem situation. Number Community type Longitude and latitude Description of ecosystem HW1 Beaches bare land N37˚43'4" E119˚13'45" The major land use is tidal flats, and scattered vegetation such as Phragmites australi and willow, height of 0.5 - 1 m. HW2 Suaeda salsa N37˚45'55" E119˚08'50" The vegetation types are Suaeda salsa and Phragmites australi. HW3 Phragmites australis N37˚45'2" E119˚7'43" The vegetation type is phragmites australis community, mainly including Phragmites australis, Suaeda salsa, Tamnrix chinesi and wild chrysanthemum, with 2 cm layer of litter at the surface. HW4 Tamnrix chinesi N37˚46'04.6" E119˚09'27.1" HW5 Farmland N37˚46'2" E118˚55'38" The vegetation type is community of Tamnrix chinesi-Phragmites australi, and 80% of cover degree. There are oilfield pipelines and vehicles and other human activities around. The vegetation type is cotton. 2.4. Date Analysis The size of the static opaque chamber is 100 cm × 100 cm × 60 cm. The static opaque chamber method was used to measure CH4 and CO2 flux. The concentrations of CH4 and CO2 were determined with infrared carbon dioxide analyzer or G-C. The sampling time was 0, 20, 40, 60, 90, 120 min in 120 min sample period. At the same time, the temperature, air pressure and the concentration of CO2 were measured in the static opaque chamber. CH4 and CO2 flux was calculated by using the following formula [15]. J= dc M P T0 ⋅ ⋅ ⋅ ⋅H dt V0 P0 T where J represents the gas flux (mg∙m−2∙h−1); dc/dt is the straightslope for the gas concentration at the time change of sampling; M is molar mass of gas to be measured; P is the pressure in sampling site; T is the absolute temperature; V0, P0, T0 are molar volume of gas, air pressure and absolute temperature under the standard state condition; H is the height of sampling box above the water surface. The load of annual emissions was calculated by using the following estimation formulas: 29 Q. F. Chen et al. L = J ⋅ S ⋅ 24 h ⋅ 365 d ⋅10−6 where L represents the load of annual emissions (t∙a−1); J is the mean gas flux (mg∙m−2∙h−1); S is the zone area (m2). 3. Results and Discussion 3.1. The Variation Characteristics of CH4 and CO2 Emission Flux under Different Seasons Five different plant communities were selected to monitor the carbon emissions on-site under different seasons. The emissions flux of CH4 and CO2 in different kinds of salt marsh plant communities was calculated. The results were shown in Figure 3. The results of CH4 and CO2 emission flux presented distinct season diversity in the spring and autumn. In the spring, CO2 emission flux was higher than that in the autumn, and appeared negative in HW3 and HW4 in the autumn. CH4 emission flux of HW4 and HW5 was negative in the spring and autumn, which indicated that the CH4 emission process was net absorption. 3.2. The Variation Characteristics of CH4 and CO2 Emission Flux under Different Years The emissions flux of CH4 and CO2 in different kinds of salt marsh plant communities was calculated under different years. The results were shown in Figure 4. From the Figure 4, emission fluxes of CO2 were all positive in 2011, performance for carbon emissions. But emission flux of CH4 was all negative in 2011, showing the net carbon absorption. Except for HW2 and HW5, the emission flux of CH4 was contrary to that of CO2 in 2012. The emission flux of CH4 was contrary to that of CO2 for HW4 and HW5 in 2013. 3.3. The Variation Characteristics of CH4 and CO2 Emission Flux under Different Land Use Types CO2 emission flux of HW3 and HW4 was opposite in the spring and autumn (Figure 5). The performance of HW3 and HW4 for CO2 emission was released in the spring, and performance for carbon sequestration in the autumn. While other land use types, the CO2 emission flux was characterized by carbon emissions. CH4 emission flux of HW4 and HW5 was all negative in the spring and autumn. While for other land use types, emission flux of CH4 was characterized by net carbon emissions. From the Figure 6, the results of CH4 and CO2 annual emission flux presented distinct space diversity under different land use types. Among the 5 kinds of land use types, the HW4 discharged the largest emission flux of CO2 reaching 29.3 mg∙m−2∙h−1. It can be concluded that the emission flux of CO2 was increased by the human activities. The emission flux of CO2 was distinct because of the large hydrological change of Yellow River’s water level, which made the soil condition of oxidation and reduction alternately changed frequently. The order of CO2 emission flux: HW4 > HW5 > HW1 > HW2 > HW3. Except for CO2 emission flux of HW1 and HW3 was 0.4 HW1 HW2 HW3 HW4 HW5 CO2 (mg/m-2/h-1) 20 10 0 -10 spring HW1 HW2 HW3 HW4 HW5 0.3 CH4 (mg/m-2/h-1) 30 autumn 0.2 0.1 0.0 spring Time -0.1 -20 -0.2 Figure 3. The variation characteristics of CH4 and CO2 emission flux under different seasons. 30 autumn Time Q. F. Chen et al. 50 HW1 HW2 HW3 HW4 0.40 HW5 HW1 HW2 HW3 HW4 HW5 0.35 40 0.30 0.25 CH4(mg/m-2/h-1) CO2 (mg/m-2/h-1) 30 0.20 20 0.15 10 0.10 0 2011 2012 0.05 2013 -10 0.00 -20 -0.05 2011 -30 2012 2013 -0.10 year year -0.15 Figure 4. The variation characteristics of CH4 and CO2 emission flux under different years. 0.5 30 Spring autumn 0.4 Spring autumn -1 CH4 (mg/m /h ) 0.3 -2 CO2 (mg/m-2/h-1) 20 10 0 HW1 HW2 HW3 HW4 HW5 0.2 0.1 0.0 Sample site -10 HW1 HW2 HW3 HW4 HW5 Sample site -0.1 -20 -0.2 Figure 5. The seasonal variation characteristics of CH4 and CO2 emission flux under different land use types. 0.4 50 40 2011 2012 2013 2011-2013 0.3 CH4 (mg/m-2/h-1) CO2 (mg/m-2/h-1) 30 2011 2012 2013 2011-2013 0.2 20 0.1 10 0 HW1 HW2 -10 HW3 HW4 0.0 HW5 HW1 HW2 HW3 HW4 HW5 Sample site -0.1 -20 -30 -0.2 Sample site Figure 6. The annual variation characteristics of CH4 and CO2 emission flux under different land use types. negative in 2012, the others were all positive. Among the 5 kinds of land use types, the HW2 discharged the largest emission flux of CH4, reaching 0.15 mg∙m−2∙h−1. From the estuary to the inland, the emission flux of CH4 was increased at first and then showed decreasing trend. The order of CH4 emission flux: HW2 > HW1 > HW3 > HW4 > HW5. CH4 emission flux of HW4 and HW5 was negative, and showed the net carbon absorption. 4. Conclusions The greenhouse gas emission flux, especially the CO2 and CH4, showed distinctly spatial and temporal variation 31 Q. F. Chen et al. under different land use types in the Yellow River Delta Wetland. In the spring, the emission flux of CO2 was higher than that of CO2 in the autumn, and appeared negative in HW3 and HW4 in the autumn. CH4 emission flux of HW4 and HW5 was negative in the spring and autumn, which indicated that the CH4 emission process was net absorption. Among the 5 kinds of land use types, the HW4 discharged the largest emission flux of CO2, reaching 29.3 mg∙m−2∙h−1, but the HW2 discharged the largest emission flux of CH4, reaching 0.15 mg∙m−2∙h−1. From the estuary to the inland, the emission flux of CO2 was decreased at first and then showed decreasing trend, but the emission flux of CH4 was contrary to CO2. Among the 5 kinds of land use types, the order of CO2 emission flux: HW4 > HW5 > HW1 > HW2 > HW3. Except for CO2 emission flux of HW1 and HW3 was negative in 2012, the others were all positive. The order of CH4 emission flux: HW2 > HW1 > HW3 > HW4 > HW5. CH4 emission flux of HW4 and HW5 was negative and showed the net carbon absorption. Acknowledgements This study was jointly sponsored by National Natural Science Foundation of China (No. 41003033), and Major Science and Technology Program for Water Pollution Control and Treatment (2015ZX07203-005, 2015ZX07203-007). References [1] Nnoby, R. (1997) Carbon cycle: Inside the Black Box. Nature, 388, 522-523. http://dx.doi.org/10.1038/41441 [2] Sahagian, D. and Melack, J. (1998) Global Wetland Distribution and Functional Characterization: Trace Gases and the hydrologic Cycle. IGBP Report 46. [3] Han, G., Xing, Q., Yu, J., et al. (2014) Agricultural Reclamation Effects on Ecosystem CO2 Exchange of a Coastal Wetland in the Yellow River Delta. Agriculture, Ecosystems & Environment, 196, 187-198. http://dx.doi.org/10.1016/j.agee.2013.09.012 [4] IPCC (International Panel on Climate Change) (1996) Climate Change 1996—Impacts, Adaptations and Mitigation of Climate Change: Scientific Technical Analysis. Contribution of Working Group II to the Second Assessment Report of the IPCC. Cambridge University Press, Cambridge. [5] Bassi, N., Kumar, M.D., Sharma, A., et al. (2014) Status of Wetlands in India: A Review of Extent, Ecosystem Benefits, Threats and Management Strategies. Journal of Hydrology: Regional Studies, 2, 1-19. http://dx.doi.org/10.1016/j.ejrh.2014.07.001 [6] Qi, S. and Fang, L. (2007) Environmental Degradation in the Yellow River Delta, Shandong Province, China. AMBIO: A Journal of the Human Environment, 36, 610-611. http://dx.doi.org/10.1579/0044-7447(2007)36[610:EDITYR]2.0.CO;2 [7] Xu, X., Lin, H. and Fu, Z. (2004) Probe into the Method of Regional Ecological Risk Assessment—A Case Study of Wetland in the Yellow River Delta in China. Journal of Environmental Management, 70, 253-262. http://dx.doi.org/10.1016/j.jenvman.2003.12.001 [8] Liu, X.Z. and Qi, S.Z. (2011) Wetlands Environmental Degradation in the Yellow River Delta, Shandong Province of China. Procedia Environmental Sciences, 11, 701-705. http://dx.doi.org/10.1016/j.proenv.2011.12.109 [9] Qin, Y., Yang, Z. and Yang, W. (2010) A Novel Index System for Assessing Ecological Risk under Water Stress in the Yellow River Delta Wetland. Procedia Environmental Sciences, 2, 535-541. http://dx.doi.org/10.1016/j.proenv.2010.10.058 [10] Chen, Q.F., Ma, J.J., Liu, J.H., et al. (2013) Characteristics of Greenhouse Gas Emission in the Yellow River Delta Wetland. International Biodeterioration & Biodegradation, 85, 646-651. http://dx.doi.org/10.1016/j.ibiod.2013.04.009 [11] Funk, D.W., Noel, L.E. and Freedman, A.H. (2004) Environmental Gradients, Plant Distribution, and Species Richness in Arctic Salt Marsh near Prudhoe Bay, Alaska. Wetlands Ecology and Management, 12, 215-233. http://dx.doi.org/10.1023/B:WETL.0000034074.81373.65 [12] He, Q., Cui, B.S., Zhao, X.S., Fu, H.L. and Liao, X.L. (2009) Relationships between Salt Marsh Vegetation Distribution/Diversity and Soil Chemical Factors in the Yellow River Estuary. Acta Ecologica Sinica, 29, 676-686. [13] Tessier, A., Campbell, P.G.C. and Bisson, M. (1979) Sequential Extraction Procedure for the Speciation of Particulate Trace Metals. Analytical Chemistry, 51, 844-851. http://dx.doi.org/10.1021/ac50043a017 [14] APHA (2005) Standard Methods for the Examination of Water and Wastewater. 21st Edition, American Public Health Association, Washington DC. [15] Li, M. and Li, W. (2009) Review on Carbon Cycle of Wetland Ecosystem. Huazhong Agri. Univ., 28, 116-123. 32
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.